Senior Data Architect

Introduction:

The Senior Data Architect will be responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection for economic policy and research teams. The ideal candidate should have experience in data modeling, database design, data pipeline building, and data wrangling. They will play a crucial role in supporting economists and technical experts, ensuring optimal data delivery architecture is designed and developed to meet the organization''s data needs.

Responsibilities:

• Analyze data processes, applications, and source data to understand dependencies, anomalies, and business rules.
• Design, develop, and maintain robust data pipelines for ingesting, transforming, and delivering data from multiple sources.
• Architect and implement ETL/ELT workflows using modern data engineering tools for large-scale data processing.
• Create data solution designs for economic policy and research projects.
• Define specifications and implement database structures, backup procedures, and access security controls.
• Collaborate with research and business teams to improve data models and processes supporting analytics tools.
• Implement processes to monitor data quality and ensure data accuracy and availability.
• Identify and implement process improvements, automation of manual processes, and infrastructure redesign for scalability and performance.
• Participate in developing future-state data architecture standards and guidelines.

Requirements:

• Bachelor’s degree in computer science, Information Technology, Engineering, or related technical field.
• At least 7 years of related experience; advanced degree preferred.
• Advanced working knowledge of SQL and relational database platforms (e.g., PostgreSQL, Microsoft SQL Server, MySQL).
• Experience with Python, R, and other scripting languages for data engineering and analytics.
• Experience with large-scale data systems, distributed computing, and data storage architecture.
• Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines.
• Experience with workflow orchestration tools like Apache Airflow, Prefect, Dagster, or AWS Step Functions.
• Experience migrating workflows and data pipelines between on-premises and cloud environments.
• Experience processing and integrating structured and unstructured data sources.
• Experience with Linux environments, source control platforms (e.g., GitLab, GitHub), and root cause analysis.
• Strong communication skills, analytical abilities, problem-solving, and troubleshooting skills.

Additional Desirable Skills/Experience:

• Understanding of time series data and forecasting techniques.
• Experience in a research environment or with economic/financial data.
• Knowledge of NoSQL and graph database technologies.
• Experience with machine learning models, cloud technologies (AWS, Microsoft Azure, Snowflake), CI/CD pipelines, and DataOps platforms.
• Working knowledge of programming languages like Java, Scala, JavaScript, or Perl.